Oracle Enterprise Data Quality: Match and Parse

This course (based on Oracle Enterprise Data Quality version 9.0) teaches the participants how to configure match processors to find and optionally merge exact and similar (fuzzy) matching records. Participants learn how to create sophisticated match rule hierarchies, configure merge options and review match results. This offering also deals about the different match processors that are available, including those in the Customer Data Extension Pack. Participants also learn to standardize data and see how this can be used to prepare data for matching.

In addition this course introduces the participants to Oracle Enterprise Data Quality's transliteration capabilities and shows how to use and interpret results from the Oracle Enterprise Data Quality Address Verfication server. Participants learn to reach a semantic understanding of free text by using the Phrase Profiler. They also learn techniques to tailor a Customer Data Extension Pack parse processor to extract, standardize and re-structure data from a free text field and also to configure the Parse processor from scratch.

Learn To:

• Configure match processors to identify and optionally merge matching records
• Use Parse processors to extract key data from free text fields
• Use the Address Verification processor and interpret its results
• Standardize data using a number of Oracle Enterprise Data Quality processors

This course is based on Oracle Enterprise Data Quality version 9.0.2 .

Audience

• Business Intelligence Developer
• Data Warehouse Administrator
• End Users
• Functional Implementer
• Reports Developer
• Sales Consultants
• Technical Consultant
• System Analysts

Course Topics Match Overview

• Discussing Business Examples of Matching
• About the Match Processors
• What Constitues a Match?

Oracle Enterprise Data Quality Matching Fundamentals

• Discussing Inputs to Match
• About Mapping Identifiers
• Discussing Fundamentals of Clustering
• Setting up Simple Match Rules
• Browsing Results

Match Rule Hierarchies

• Using Multiple Comparisons
• Identifying Fuzzy (inexact) Matches
• Tuning Match Rules

Clustering

• Clustering for Performance
• Clustering Strategies
• Tuning Clusters

Merge

• Discussing Defaults for Merging
• Merging Options

Match Review

• Discussing Review Groups
• About the Match Review Interface

Customer Data Extension Pack Match Processors

• About the Match Entities processor
• About the Match Individuals processors
• About the Match Households processor

Match Case Studies

• Enhancing Records
• Describing Deduplication

Address Verification

• Overview of Address Verification
• Using the Address Verification Processor
• About Accuracy flags: Interpreting Address Verification Results

Standardizing Data

• Overview of Standarization
• Overview of Simple Standardization
• About the Character Replace and Replace Processors
• About the Pattern Transform and RegEx Replace Processors
• About the Merge Processor
• Overview of Transliteration Capabilities

Parse Overview

• About Business Uses of Parsing
• Parsing in Oracle Enterprise Data Quality

The Phrase Profiler

• Using the Phrase Profiler
• Identifying Common Words and Phrases
• Identifying Misplaced Data

Tailoring a Customer Data Extenstion Pack Parse Profiler- Part I

• Understanding Tokenization
• Using the Classify sub processor

Tailoring a Customer Data Extenstion Pack Parse Profiler- Part II

• Using the Reclassify sub processor
• Classification vs. Reclassification

Tailoring a Customer Data Extenstion Pack Parse Profiler - Part III

• Using the Select sub processor
• Using the Resolve sub processor
• Creating Exact and Fuzzy Resolution Rules

Parsing from the Ground Up

• Profiling and Classification
• Reclassification, Selection and Resolutions

Optional- Case Studies

• Discussing Parse Case Study
• Discussing Overall Enterprise Data Quality Case Study

Course Objectives

• Use the Address Verification processor and interpret its results
• Use transformation processors to standardize data
• Configure parse processors.
• Tailor parse and match processors from the Customer Data Extension Pack
• Explain the need and uses of matching
• Explain the need and uses of parsing
• Use the Phrase Profiler
• Explain the essentials of matching and parsing.
• Cofigure match processors to identify and if necessary, consolidate matching data records